AI SEO Statistics: Tattoo Shop (2026-07 edition)

Reading the 45 answers model by model shows how differently the three assistants treat the same tattoo shop questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 60% (ChatGPT) down to 53.3% (Gemini), a 7-point gap on an identical question set.

Across the 15 tattoo shop answers it produced, ChatGPT recommended hiring a professional in 60% of them and suggested a DIY approach first 0% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 6.7% of the time. ChatGPT asked a clarifying question before answering in 53.3% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 20%, averaging 472 words per answer. On the remaining cues it told the buyer to check reviews in 26.7%, pointed to case studies or a portfolio in 40%, and framed the choice around local proximity in 20%; a selection-criteria checklist appeared in 53.3% of its answers and a recommendation to gather multiple quotes in 20%.

Across the 15 tattoo shop answers it produced, Claude recommended hiring a professional in 60% of them and suggested a DIY approach first 0% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 0% of the time. Claude asked a clarifying question before answering in 53.3% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 13.3%, averaging 268 words per answer. On the remaining cues it told the buyer to check reviews in 40%, pointed to case studies or a portfolio in 46.7%, and framed the choice around local proximity in 13.3%; a selection-criteria checklist appeared in 66.7% of its answers and a recommendation to gather multiple quotes in 13.3%.

Across the 15 tattoo shop answers it produced, Gemini recommended hiring a professional in 53.3% of them and suggested a DIY approach first 0% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 20% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 6.7%, and told the buyer to verify credentials in 6.7%, averaging 284 words per answer. On the remaining cues it told the buyer to check reviews in 6.7%, pointed to case studies or a portfolio in 26.7%, and framed the choice around local proximity in 6.7%; a selection-criteria checklist appeared in 46.7% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a tattoo shop buyer to a professional (60%) and Gemini the least (53.3%). ChatGPT produced the longest answers, at 472 words on average. No model named a specific provider in more than 0% of answers.

On other behaviors the three models move almost in lockstep — the points of near-consensus for tattoo shop, where all three landed within a few points of each other:

• Suggests a DIY approach first: 0% across all three models.
• Names a specific provider: 0% across all three models.
• Recommends hiring a professional: 53.3%–60% across all three (a 7-point spread).
• Tells the buyer to verify credentials: 6.7%–20% across all three (a 13-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "suggests a DIY approach first" (identical coding in 100% of questions) and least consistently on "asks a clarifying question" (33.3%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the tattoo shop buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 24.5% of answers on average. Verifying credentials or certifications appeared in 13.3%. Warning about red flags or scams appeared in 15.6%.

On structuring the decision, a selection-criteria checklist showed up in 55.6% of answers on average and a recommendation to gather multiple quotes in 11.1%. The single least-reproduced protective signal for tattoo shop is "recommends multiple quotes" at 11.1% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

The 15 questions behind every percentage on this page were drawn from real tattoo shop (beauty services; buyer hiring decisions for this specific service) buyer journeys. Each was put to all 3 models once, with identical wording, so the rates above describe how the assistants handled this exact tattoo shop question set — not a general prior or a hand-picked subset. The full list is shown earlier on this page; the coded percentages are what those specific questions produced.